Embodiments of the invention relate generally to diagnostic imaging and, more particularly, to a system and method of pulmonary emboli detection for computed tomography.
Typically, in computed tomography (CT) imaging systems, an x-ray source emits a fan-shaped beam toward a subject or object, such as a patient or a piece of luggage. Hereinafter, the terms “subject” and “object” shall include anything capable of being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at the detector array is typically dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the detector array produces a separate electrical signal indicative of the attenuated beam received by each detector element. The electrical signals are transmitted to a data processing system for analysis which ultimately produces an image.
Generally, the x-ray source and the detector array are rotated about the gantry within an imaging plane and around the subject. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal point. X-ray detectors typically include a collimator for collimating x-ray beams received at the detector, a scintillator for converting x-rays to light energy adjacent the collimator, and photodiodes for receiving the light energy from the adjacent scintillator and producing electrical signals therefrom.
Typically, each scintillator of a scintillator array converts x-rays to light energy. Each scintillator discharges light energy to a photodiode adjacent thereto. Each photodiode detects the light energy and generates a corresponding electrical signal. The outputs of the photodiodes are then transmitted to the data processing system for image reconstruction. Alternatively, x-ray detectors may use a direct conversion detector, such as a CZT detector, in lieu of a scintillator.
Contrast enhanced CT images are typically used to detect pulmonary embuli within the pulmonary vessels. Simple thresholds, linear contrast enhancements, intensity information, and/or knowledge of the neighborhood of image voxels are typically used to generate contrast enhanced CT images. Alternatively, large banks of information acquired from a large number of CT images may be used to train classifiers, which are then used to predict whether identified or calculated features or characteristics of three-dimensional regions in an image represent pulmonary embuli or normal anatomy.
Conventional methods of generating contrast enhanced CT images typically rely on a number of assumed features of pulmonary embuli. However, these assumptions often detect normal anatomy as pulmonary emboli (i.e., false positives). False positives may be detected due to a number of causes, including lymph nodes, water-filled airways, airway walls with intermediate intensity resulting from partial volume effects, motion, streak and/or other acquisition artifacts, and images of inadequate contrast resulting from improperly administered contrast schedules, for example.
Therefore, it would be desirable to design a system and method of detecting pulmonary emboli that overcome the aforementioned drawbacks.